code: def _test_bert(self, virtual_pipeline_model_parallel_size):
      self.MANUAL_SEED = 42
      self.inds = None
      self.masks = None
      self.data_idx = 0
      self.MASK_PROB = 0.1
      self.EASY_MODE = False
      self.EASY_MODE_SIZ = 32
  
      tensor_model_parallel_size = (
          2 if self.world_size % 2 == 0 and self.world_size > 4 else 1
      )
      pipeline_model_parallel_size = (
          self.world_size // tensor_model_parallel_size
      )
  
      override_args = {
          "micro_batch_size": 2,
          "num_layers": 16,
          "hidden_size": 256,
          "num_attention_heads": 8,
          "max_position_embeddings": 512,
          "seq_length": 512,
          "global_batch_size": 128,
          "pipeline_model_parallel_size": pipeline_model_parallel_size,
          "tensor_model_parallel_size": tensor_model_parallel_size,
          "bert_binary_head": False,
          "world_size": self.world_size,
          "rank": self.rank,
      }
  
      global_vars.set_global_variables(
          override_args=override_args, ignore_unknown_args=True
      )
      args = global_vars.get_args()
  
      self.fancy_data = self._download_fancy_data()
      self.effective_length = self.fancy_data.size(0) // args.seq_length
      self.effective_length = self.fancy_data.size(0) - args.seq_length
  
      if self.rank == 0:
          print(
              f"testing backend: {self.DISTRIBUTED_BACKEND} with virtual_pipeline_model_parallel_size: {virtual_pipeline_model_parallel_size}"
          )
      async_comm = (
          not args.sequence_parallel
          and virtual_pipeline_model_parallel_size is None
      )
      self.data_idx = 0
      args.padded_vocab_size = 128  # needed in standalone gpt
      args.model_type = ModelType.encoder_or_decoder
      setup_microbatch_calculator(
          args.rank,
          args.rampup_batch_size,
          args.global_batch_size,
          args.micro_batch_size,
          args.data_parallel_size,
      )
      parallel_state.initialize_model_parallel(
          args.tensor_model_parallel_size,
          args.pipeline_model_parallel_size,
          virtual_pipeline_model_parallel_size,
          default_backend="nccl",
          p2p_backend=self.DISTRIBUTED_BACKEND,
      )
  
      tensor_parallel.random.model_parallel_cuda_manual_seed(0)
      model = build_model(
          bert_model_provider,
          wrap_with_ddp=parallel_state.get_data_parallel_world_size()
          > 1,
          virtual_pipeline_model_parallel_size=virtual_pipeline_model_parallel_size,
          cpu_offload=args.cpu_offload,
      )
      assert isinstance(model, list)
      assert len(model) == (
          1
          if virtual_pipeline_model_parallel_size is None
          else virtual_pipeline_model_parallel_size
      )
      _param_groups = _get_params_for_weight_decay_optimization(model)
      optim = torch.optim.Adam(_param_groups)
      self._train(
          model,
          optim,
          virtual_pipeline_model_parallel_size,
          args.pipeline_model_parallel_size,
          async_comm,
      )
      torch.cuda.synchronize()
  
imports: import torch
  import unittest
  from apex.transformer.testing import global_vars
  from apex.transformer.testing.standalone_bert import bert_model_provider
  from apex.transformer.pipeline_parallel.schedules.common import _get_params_for_weight_decay_optimization, build_model
  from apex.transformer.pipeline_parallel.schedules import get_forward_backward_func
  from apex.transformer.pipeline_parallel.utils import average_losses_across_data_parallel_group, unwrap_model, setup_microbatch_calculator
  from apex.transformer.log_util import set_logging_level
  from apex.transformer import tensor_parallel, parallel_state
  from apex.transformer.enums import ModelType
  from apex.transformer._ucc_util import HAS_UCC
  from apex.transformer.testing.distributed_test_base import UccDistributedTestBase, NcclDistributedTestBase
  import logging
  from torch.testing._internal import common_utils
label_desc: Use image node_id 7 for calling the BertTestBase obj's underlying member method code with example usage: obj._test_bert(virtual_pipeline_model_parallel_size) without return types